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Record W2368193714

Improvement to MVFAST Motion Estimation Algorithm and VLSI Architecture

2008· article· en· W2368193714 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Technology and Development · 2008
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsComputer scienceMotion estimationAlgorithmArchitectureSearch algorithmBandwidth (computing)Image qualityVery-large-scale integrationImage processingArtificial intelligenceImage (mathematics)Computer visionReal-time computingEmbedded system
DOInot available

Abstract

fetched live from OpenAlex

Improvement to the search window of MVFAST algorithm is proposed,on the basis of analyzing MVFAST algorithm.By its improvement,and in the guarantee of image quality,the search speed of algorithm is improved.Designs the architecture and processing element.At the same time,the architecture for flexible data flow and search strategy is proposed.Tests different video sequences,video sequences on different resolution and video sequences on different motion degree,experiment results verify that the processing speed of the architecture is improved obviously,the memory accessing bandwidth is reduced dramatically,and its image quality is similar to the full search algorithm.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.997
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.225
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it